Every restaurant owner knows the feeling. It is 4:47 p.m., the dinner rush is warming up, 2 people call out, 1 never confirmed, and the POS is blinking like it is trying to send smoke signals. Labor is your biggest line item and somehow the least predictable. Welcome to the hourly economy, where spreadsheets pray and managers improvise in real time.
Now enter Ando, out of San Francisco, building AI infrastructure for the global hourly workforce. Not another scheduling app with prettier colors, but true infrastructure, the pipes under the building and the grid behind the grid. Ando just secured new funding to make hourly work more predictable, and that word predictable is doing real work. Demand forecasting, intelligent scheduling, and a persistent labor graph for hourly W-2 workers form a living data layer that understands who shows up, who performs, who prefers Tuesdays at 3 p.m., and who thrives in the chaos of Saturday night.
This is about turning labor from guesswork into signal. At the center is Founder and CEO Paul Wellons, who has clearly spent enough time in the trenches to know that hourly work is not a line on a P and L, it is the engine. Under Paul Wellons’ leadership, Ando is building predictive demand models that inform staffing before the rush hits, intelligent scheduling that allocates shifts with context, and a labor graph that compounds value over time, creating data that remembers and systems that learn.
The funding backs a platform focused on 3 pillars: demand forecasting that sees around corners, intelligent scheduling that matches real people to real shifts with nuance, and a persistent labor graph that transforms hourly work history into something durable. Think of it as a credit score for work ethic, minus the bureaucracy and with a lot more upside, where every completed shift strengthens a worker’s professional identity instead of disappearing into the void.
For operators, this means fewer fire drills and tighter margins. For workers, it means visibility, mobility, and a shot at consistency in a world that rarely offers it, with predictable hours, smarter matches, and less chaos dressed up as hustle. Ando is not chasing vanity metrics; it is building a system where every shift teaches the model something new, every clock-in sharpens the graph, and every schedule becomes less of a gamble and more of a decision.
In an economy powered by hourly talent, the real innovation is not another app icon, it is infrastructure that treats labor like the asset it has always been. If Ando gets this right, the phrase “Who can cover tonight?” might finally lose its edge, and predictability might stop being a luxury and start becoming the standard.
